首页> 外文会议>International Workshop on Intelligent Computing in Pattern Analysis/Synthesis(IWICPAS 2006); 20060826-27; Xi'an(CN) >Motion and Gray Based Automatic Road Segment Method MGARS in Urban Traffic Surveillance
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Motion and Gray Based Automatic Road Segment Method MGARS in Urban Traffic Surveillance

机译:城市交通监控中基于运动和灰色的自动路段划分方法

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摘要

This paper presents a novel method MGARS to automatic road area segmentation based on motion and gray feature for the purpose of urban traffic surveillance. The proposed method can locate road region by region growing algorithm with the fusion feature of motion information and grayscale of background image, which is independent to road marker information. An adaptive background subtraction approach using gray information is performed to motion segmentation. In region growing stage, start point that so called seed is selected automatically by motion centroid and local gray feature of background image. The threshold of region growing method is adaptively selected for different traffic scenes. The proposed method MGARS can effectively segment multi roads without manual initialization, and is robust to road surface pollution and tree shadow. The system can adapt to the new environment without human intervention. Experimental results on real urban traffic videos have substantiated the effectiveness of the proposed method.
机译:提出了一种基于运动和灰度特征的MGARS自动道路区域分割方法,用于城市交通监控。该方法可以通过区域增长算法来定位道路区域,该算法具有运动信息和背景图像灰度的融合特征,而与道路标志信息无关。使用灰色信息的自适应背景扣除方法被执行以进行运动分割。在区域生长阶段,通过运动质心和背景图像的局部灰度特征自动选择所谓的种子的起点。针对不同的交通场景自适应选择区域增长方法的阈值。提出的方法MGARS可以有效地分割多条道路,而无需人工初始化,并且对路面污染和树影具有鲁棒性。该系统无需人工干预即可适应新环境。在真实的城市交通视频上的实验结果证实了该方法的有效性。

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